Sphere Detection in Kinect Point Clouds via the 3D Hough Transform

We introduce a fast, robust and accurate Hough Transform (HT) based algorithm for detecting spherical structures in 3D point clouds. To our knowledge, our algorithm is the first HT based implementation that detects spherical structures in typical in 3D point clouds generated by consumer depth sensors such as the Microsoft Kinect. Our approach has been designed to be computationally efficient; reducing an established limitation of HT based approaches. We provide experimental analysis of the achieved results, showing a robust performance against occlusion, and we show superior performance to the only other HT based algorithm for detecting spheres in point clouds available in literature.